Open University of Catalonia

About: Open University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Context (language use) & Higher education. The organization has 1943 authors who have published 4646 publications receiving 64200 citations. The organization is also known as: Universitat Oberta de Catalunya & UOC.

Cherry‐picking participation: Explaining the fate of proposals from participatory processes

Abstract: What happens to the proposals generated by participatory processes? One of the key aspects of research on public participation that has been the subject of rare systematic analysis and comparison is the fate of the output from participatory processes: their proposals. Which specific factors explain whether proposals are accepted, rejected or transformed by public authorities? This paper contributes to this gap in our understanding in two steps. First, we identify contextual, process and proposal related factors that are likely to affect the prospect of proposals being implemented, generating a set of testable hypotheses. Second, we test the explanatory power of these hypotheses through multilevel analysis on a diverse set of 571 policy proposals. Our findings offer evidence that while there is no effect for contextual factors, both process and proposal related variables have significant explanatory power. The design of participatory processes affects the degree of implementation, with participatory budgeting and higher quality processes being particularly effective. But most significant for explaining implementation are proposal level economic and political factors: a proposal's cost, the extent to which it challenges existing policy and the degree of support it has within the municipality all strongly affect the chance of implementation.

Gradient-Based Optimizer for Parameter Extraction in Photovoltaic Models

Abstract: Solar radiation is increasingly used as a clean energy source, and photovoltaic (PV) panels that contain solar cells (SCs) transform solar energy into electricity. The current-voltage characteristics for PV models is nonlinear. Due to a lack of data on the manufacturer’s datasheet for PV models, there are several unknown parameters. It is necessary to accurately design the PV systems by defining the intrinsic parameters of the SCs. Various methods have been proposed to estimate the unknown parameters of PV cells. However, their results are often inaccurate. In this article, a gradient-based optimizer (GBO) was applied as an efficient and accurate methodology to estimate the parameters of SCs and PV modules. Three common SC models, namely, single-diode models (SDMs), double-diode models (DDMs), and three-diode models (TDMs) were used to demonstrate the capacity of the GBO to estimate the parameters of SCs. The proposed GBO algorithm for estimating the optimal values of the parameters for various SCs models are applied on the real data of a 55 mm diameter commercial R.T.C-France SC. Comparison between the GBO and other algorithms are performed for the same data set. The smallest value of the error between the experimental and the simulated data is achieved by the proposed GBO. Also, high closeness between the simulated P-V and I-V curves is achieved by the proposed GBO compared with the experimental.

MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems

Abstract: This paper discusses the use of probabilistic or randomized algorithms for solving vehicle routing problems with non-smooth objective functions. Our approach employs non-uniform probability distributions to add a biased random behavior to the well-known savings heuristic. By doing so, a large set of alternative good solutions can be quickly obtained in a natural way and without complex configuration processes. Since the solution-generation process is based on the criterion of maximizing the savings, it does not need to assume any particular property of the objective function. Therefore, the procedure can be especially useful in problems where properties such as non-smoothness or non-convexity lead to a highly irregular solution space, for which the traditional optimization methods—both of exact and approximate nature—may fail to reach their full potential. The results obtained so far are promising enough to suggest that the idea of using biased probability distributions to randomize classical heuristics is a powerful one that can be successfully applied in a variety of cases.

From needs analysis to task design: Insights from an English for specific purposes context

Abstract: Needs analysis (NA) has long been argued to be the prerequisite for the design of language curricula or syllabi and the selection of tasks. According to Long (2005), a one-size-fits-all approach should be substituted by a careful examination of learners’ needs in a particular domain or learner community. Despite the increasing practice of carrying out a NA as a first step in curriculum design, it is still unclear how exactly the insights obtained from NA can be used in meaningful ways to take informed decisions about task and syllabus design. This study attempts to fill this gap by applying the findings obtained in a NA in the domain of a hotel receptionist’s job to the design of pedagogic tasks. The goals of this study were to obtain insights into what tasks are done in this domain (task selection), what kind of language use is associated with these tasks (task discourse analysis), how the information about perceived difficulty of tasks can be translated into instructionally manipulable variables (task d...